Journal of Computer Applications ›› 2020, Vol. 40 ›› Issue (2): 479-485.DOI: 10.11772/j.issn.1001-9081.2019081612

• CCF NDBC 2019 • Previous Articles     Next Articles

Preventing location disclosure attacks through generating dummy trajectories

Xiangyu LIU1,2(), Jinmei CHEN1, Xiufeng XIA1, Manish Singh2, Chuanyu ZONG1, Rui ZHU1   

  1. 1.College of Computer Science,Shenyang Aerospace University,Shenyang Liaoning 110136,China
    2.School of IT and Business,Wellington Institute of Technology,Lower Hutt 5010,New Zealand
  • Received:2019-08-14 Revised:2019-08-27 Accepted:2019-10-12 Online:2019-11-18 Published:2020-02-10
  • Contact: Xiangyu LIU
  • About author:CHEN Jinmei, born in 1994, M. S. candidate. Her research interests include data privacy protection.
    XIA Xiufeng, born in 1964, Ph. D., professor. His research interests include database, data warehouse, data mining.
    Manish Singh, born in 1981, Ph. D. candidate, senior lecturer. His research interests include parallel computing, cryptography.
    ZONG Chuanyu, born in 1985, Ph. D., lecturer. His research interests include data cleaning, tracing the source of data, optimization of query processing.
    ZHU Rui, born in 1982, Ph. D., lecturer. His research interests include data stream.
  • Supported by:
    the Key Projects of Natural Science Foundation of Liaoning Province(20170520321)

防止暴露位置攻击的轨迹隐私保护

刘向宇1,2(), 陈金梅1, 夏秀峰1, Singh Manish2, 宗传玉1, 朱睿1   

  1. 1.沈阳航空航天大学 计算机学院,沈阳 110136
    2.惠灵顿理工学院 信息与商科学院,新西兰 下哈特 5010
  • 通讯作者: 刘向宇
  • 作者简介:陈金梅(1994—),女,河北张家口人,硕士研究生,主要研究方向:数据隐私保护
    夏秀峰(1964—),男,山东胶南人,教授,博士,CCF会员,主要研究方向:数据库、数据仓库、数据挖掘; Manish Singh(1981—),男,尼泊尔人,高级讲师,博士研究生,主要研究方向:并行计算、密码学
    宗传玉(1985—),男,山东潍坊人,讲师,博士,CCF会员,主要研究方向:数据清洗、数据溯源、查询处理优化
    朱睿(1982—),男,辽宁沈阳人,讲师,博士,CCF会员,主要研究方向:数据流。
  • 基金资助:
    辽宁省自然科学基金计划重点项目(20170520321)

Abstract:

In order to solve the problem of trajectory privacy leakage caused by the collection of numerous trajectory information of moving objects, a dummy trajectory-based trajectory privacy protection algorithm was proposed. In this algorithm, considering the user’s locations under disclosure, a heuristic rule was designed based on the comprehensive measure of trajectory similarity and location diversity to select the dummy trajectories, so that the generated dummy trajectories were able to effectively hide the real trajectory and sensitive locations. Besides, the trajectory directed graph strategy and the grid-based map strategy were proposed to optimize the execution efficiency of the algorithm. Experimental results on real trajectory datasets demonstrate that the proposed algorithm can effectively protect the real trajectory with high data utility.

Key words: trajectory privacy protection, dummy trajectory, data publishing, anonymization, data utility

摘要:

为解决移动对象轨迹信息被大量收集所导致的轨迹隐私泄露问题,提出了基于假轨迹的轨迹隐私保护算法。在该算法中,考虑了用户的暴露位置,基于轨迹相似性和位置多样性的综合度量,设计了一种启发式规则来选择假轨迹,从而使得生成的假轨迹能有效隐匿真实轨迹和敏感位置。此外,还提出了轨迹有向图策略和基于网格划分的地图策略来优化算法的执行效率。基于真实的轨迹数据进行实验测试和分析,实验结果表明所提算法在保持数据可用性的情况下能有效保护真实轨迹。

关键词: 轨迹隐私保护, 假轨迹, 数据发布, 匿名化, 数据可用性

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